Comparison of LDL-C calculation by Martin, Sampson and old Friedewald methods in real data and synthetic data set.

Rudolf Gaško

Vnitrni lekarstvi 2021

filter terms:

LDL-cholesterol (LDL-C) is determined by methods whose accuracy is significantly affected in various clinical or analytical situations. Two computational methods have recently been described, the Martin equation and the Sampson equation, validity of which we compare with the Friedewald equation. LDL-C comparisons determined by the 3 equations were performed on 4 real sets of lipid data, generated in various previous studies, ranging from n = 140 to n = 7 393. We have created an artificial set of data on the extent of 900 members with equally distributed values of TC, HDL-C and TG troughout the commonly found range. Such a data set is independent of the phrase "we performed the calculations on our file". Comparisons were also made on this artificial file. The difference between the LDL-C values determined by the different equations gradually increases with decreasing LDL-C levels, both in the subgroup of low TG values and in the subgroups of medium and higher TG values. This applies to all 4 real files as well as to the artificial file. These differences are more visible the larger the file size. For the artificial set, the overall agreement between the LDL-C categories was lowest when comparing the Friedewald and Martin equations (83.1%), higher between the Sampson and Martin equations (88.9%) and highest when comparing the Friedewald and Sampson equations (90.9%). In all 4 real sets, the trends of overestimation and underestimation between the equations were exactly the same as in the artificial set. The results of clinical and epidemiological studies are significantly influenced by the method used to determine LDL-C. When comparing the calculation methods for determining LDL-C, it is possible to preferably use the described artificial set.

Citation

Rudolf Gaško. Comparison of LDL-C calculation by Martin, Sampson and old Friedewald methods in real data and synthetic data set. Vnitrni lekarstvi. 2021;67(E-2):9-17